Gun Detection System for Surveillance Cameras Using HOG-Assisted KNN Classifier

Mass shootings have become a norm in public places claiming thousands of innocent civilian lives. Firearm-related violence has been rampant in the last few decades and therefore, needs to be addressed immediately. This research aims to propose a weapon detection system that combines image processing techniques with the most suitable machine learning classifier. The experimental study has been executed in twofold: by providing a comparative analysis with previous study and with other existing algorithms as well. Results of the trained model on the dataset provide an accuracy of 98.7% which is significantly better than others published recently.